FULL LABOR PAPER FIX

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

I i

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APINDO Policy Series

Acknowledgement

Dewan Redaksi
Pelindung

: Sofjan Wanandi

Pembina

: Chris Kanter
Suryadi Sasmita
Shinta Widjaja Kamdani

Anthony Hilman

Pemimpin Redaksi : P. Agung Pambudhi
Tim Penyusun

: Diana M. Savitri
Riandy Laksono
M. Rizqy Anandhika
Sehat Dinati Simamora
I.B.P. Angga Antagia
Jefri Butarbutar
Adrinaldi

APINDO–EU ACTIVE working papers are issued in joint cooperation
between Indonesia Employer Association (APINDO) and Advancing
Indonesia’s Civil Society in Trade and Investment (ACTIVE), a
project co-funded by the European Union. ACTIVE project aims
to strengthen APINDO’s policy making advocacy capabilities in
preparing the business environment and to empower national
competitiveness in facing global integration.

For more information, please contact ACTIVE Team
at active@apindo.or.id or visit www.apindo.or.id

Wahyu Handoko
Penyunting

: Septiyan Listiya Eka R.

APINDO-EU ACTIVE Project Team Members:
Maya Safira (Project Manager)
Riandy Laksono (Lead Economist)
Muhammad Rizqy Anandhika (Economist)
Sehat Dinati Simamora (Junior Economist)
Nuning Rahayu (Project Assistant)

Copyright©APINDO-EU ACTIVE
Labor Movement from Low To High Productivity Sectors: Evidence from
Indonesian Provincial Data
Published in July 2014

D i s c l a i m er
The content of APINDO-EU ACTIVE working papers is the sole responsibility of the
author(s) and can in no way be taken to relect the views of Indonesia Employers
Association (APINDO) or its partner instututions. APINDO-EU ACTIVE working papers
are preliminary documents posted on the APUNDO website (www. apindo.or.id)
and widely circulated to stimulate discussion and critical comment.

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

Foreword

P

roductivity issues become crucial in every business and economic progress in developing countries.
Indonesia, one of the next big-player in world economy, cannot ignore the importance to improve
the productivities, including it labor productivities. In the condition of lagging productivities
among ASEAN Countries, addressing labor productivities issue is urgent in order evaluate and improve
our industries’ capability to compete in ASEAN Economic Community starting in 2015 and beneit our
decades of demographic dividend.

This second edition of APINDO Policy Series brings the productivity issue, particularly structural change as
a channel to gain productivity growth. The research about the changes of productivity across Indonesian
provinces becomes a signiicant input for industrial strategies, especially in this decentralized governance
era. It maps which provinces gain and loss the productivity, as well as which sector allocates more or less
labor, as a measure of productivity. It also tends to explain some determinant that related with structural
change.
As the employer organization concerning the employer interests, this paper should ofer a signiicant
contributions of APINDO to its stakeholder, by showing its consistency to encourage research-based
advocacy to tackle strategic issues, such as minimum wage determination. Supporting by APINDO-EU
ACTIVE Project, APINDO Policy Series hopefully can bring more industry, trade, and investment issues into
the research-based analysis to recommend suitable policies.
Finally, we appreciate APINDO-EU ACTIVE Team which deliver this policy paper and we would like to thank
Muhammad Rizqy Anandhika and Riandy Laksono for studying this issue. We hope this policy paper could
beneit Indonesian businesses in the future.

Sojan Wanandi
General Chairman
Indonesian Employers Association(APINDO)

Chris Kanter

Vice Chairman
Indonesian Employers Association(APINDO)

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iv

List of Abbreviations
AEC
ASEAN
BPS
FTA
GCI
GDP
GRP
INDO-DAPOER
ISIC
KHL

SAKERNAS

ASEAN Economic Community
Association of Southeast Asian Nations
Badan Pusat Statistik (Indonesian Statistic Agency)
Free Trade Agreement
Global Competitiveness Index
Gross Domestic Product
Gross Regional Product
Indonesia Database for Policy and Economic Research
International Standard Industrial Classiication
Kebutuhan Hidup Layak (Decent Life Component)
Survei Angkatan Kerja Nasional (National Survey of Labor Force)

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

Contents
Acknowledgement ..................................................................................................................................................................................... ii
Forewords ......................................................................................................................................................................................................... iii

List of Abbreviation ................................................................................................................................................................................. iv
Content ................................................................................................................................................................................................................ v
List of Figures ............................................................................................................................................................................................... vi
List of Tables .................................................................................................................................................................................................. vi
Abstract ............................................................................................................................................................................................................ 07
1 INTRODUCTION ........................................................................................................................................................................... 07
2 LITERATURE REVIEWS ............................................................................................................................................................ 09
3 METHODOLOgy AND DATA ............................................................................................................................................. 11
3.1 Methodology.............................................................................................................................................................................. 11
3.1.1 Structural Changes Decomposition ............................................................................................................... 11
3.1.2 Determinant of Structural Change in Indonesia, period 2001-2011 ...................................... 11
3.2 Data ................................................................................................................................................................................................ 12
4 THE RESULTS ................................................................................................................................................................................... 12
4.1 The Pattern of Productivity Growth and Structural Change in Indonesia ...................................... 12
4.2 Determinant of Structural Changes ........................................................................................................................... 15
5 Conclusion and Policy Recommendations ............................................................................................................... 19
5.1 Conclusion ................................................................................................................................................................................... 19
5.2 Policy Implications ................................................................................................................................................................ 20
5.3 Recommendation for Further Research .................................................................................................................. 21
References ....................................................................................................................................................................................................... 22

Appendices ................................................................................................................................................................................................... 23
Appendix A: 9 sectors - ISIC rev. 2 .................................................................................................................................... 23
Appendix B: Variable deinitions, sources, descriptive statistics ......................................................................24

V v

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vi

List of Figure
Figure 1

Labor Productivity of Indonesia and other ASEAN 5
countries (excluding Singapore) ..................................................................................................................... 08

Figure 2

Decomposition of Labor Productivity Growth in Indonesia 1971-2011 ............................. 12

Figure 3

Decomposition of Labor Productivity Growth
in Indonesia 1971-2011: Sectoral Figures ................................................................................................. 14

Figure 4

‘Within’ and ‘Structural Change’ Productivity Growth, 2001-2011 .............................................. 16

List of Table
Table 1

ASEAN-5’s Competitiveness world ranks in Flexibility .................................................................. 09

Table 2

Summary Statistics on Sectoral Labor Productivity ......................................................................... 16

Table 3

Summary Statistics ................................................................................................................................................. 17

Table 4

Regression results .................................................................................................................................................... 18

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

7 7

Labor Movement from Low
to High Productivity Sectors:
Evidence from Indonesia’s
Provincial Data *
M uhammad Rizqy Anandhika
Riandy Laksono
Abstract
Indonesian labor productivity faces a serious challenge ahead: its lag with the ASEAN neighbors
and ever-increasing minimum wage. To map the productivity problems, productivity growth

can be decomposed into two: (i) ‘within’ component and (ii) structural change component of
productivity growth. This paper aims to document the progress of structural change among
Indonesia’s provinces, and identiies the relevant factors behind it.
This study demonstrates that the recent structural transformation in Indonesia has not only been
slower, but also tends to left manufacturing sector behind. The inding also shows that agriculture
employment share, institution, and education are positively related to structural change, whilst
primary sector share and minimum wage growth are negatively related. In order to boost growthenhancing structural change, several policies are recommended: (1) supporting manufacturing
sector for pro-employment growth, (2) reevaluating minimum wage and other barriers of labor
lexibility, (3) promoting better access to education, (4) Diversifying economies in primary-sector
dependent provinces.
Keywords: Structural change, Indonesia, labor productivity, province

1

L

INTrODuCTION

abor productivity has become a pressing development
agenda for Indonesia, at least, for two reasons. The
irst is because Indonesian productivity is lagging
behind its neighbors. Between ASEAN countries, Indonesia’s
productivity level has not shown any signiicant changes
over time, compared to its counterparts. Amongst countries
in the Figure 1, Indonesia’s progress in productivity growth

is placed in second lowest, only better than Philippines.
In 2012, Indonesia marks 1.3 times of its productivity
compared to its 1980’s productivity, lower than Malaysia
(1.45), Singapore (1.49), Thailand (1.91), even with ASEAN
latecomers such as Cambodia (1.6) and Vietnam (2.19).
As the implementation of ASEAN Economic Community
(AEC) is near approaching, productivity issue becomes

* We want to thank to Dr. Arianto Patunru for detailed comments. Comments from seminar participants at Indonesian Development Research Workshop 2014
held by ANU Indonesia Project and SMERU Research Institute are greatly appreciated.

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FIgURE 1

Productivity changes between ASEAN countries as compared with US’s productivity, 1980=1

Productivity changes as compared with
1980=1

2.3
2.1
1.9
Indonesia
1.7

Thailand

1.5

Malaysia

1.3

Vietnam

1.1

Cambodia
Philippines

0.9

Singapore
0.7
2000
2002
2004
2006
2008
2010
2012

1990
1992
1994
1996
1998

1984
1986
1988

1980
1982

0.5

Source: The Conference Board, accessed 2014

more substantial, especially when Indonesia seeks to be
a competitive and attractive investment destination in the
pursuit of single production base of ASEAN. The igure on
productivity implies that Indonesia’s irms will face even
more diicult competition with other developing ASEAN
countries, especially in winning the ASEAN market and
attracting foreign investor.
The other important reason why Indonesia’s policy makers
should concentrate more on enhancing its productivity
is because labor productivity improvement is urgently
needed to ofset the distortive efect arising from everincreasing minimum wage in Indonesia. Having hit by the
repression of labor rights in pre-reformasi era, Indonesian
labor unions since the enactment of Manpower Protection
Law of 2003 has gained more powerful position to press
and lobby the politicians (including the government),
especially regarding labor welfare and minimum wage
increase (Chowdury et al. 2009). In line with that, the
2013-2014 global competitiveness index data shows that
Indonesia is among the most underdeveloped countries in
term of its labor market eiciency (overall rank 103rd out
of 148 economies), with extremely inlexible regime on
wage determination and very high redundancy cost (See
Table 1). Improvement on productivity could therefore
compensate the high cost incurred to employers which

is stimulated by the current ever-increasing minimum
wage regime.
The increasingly high labor cost in Indonesia will generate
a substantial high-cost business environment to the
private sectors, and is suspected as the main barrier of
massive and good employment creation. In the case
of expansion, the expensive labor cost understandably
might encourage private sectors to commit more on
technological and capital deepening, rather than hiring
more new workers (McMillan & Rodrik 2011). The data from
Badan Pusat Statistik (BPS) supports this early indication.
In 2007, it is observed that 1% economic growth could
contribute to about 700,000 new employment creation,
while in 2012, 1% of economic growth can only absorb
less than 200,000 additional workers. Furthermore, the
more disaggregated data tells that between the periods,
the major contributor of employment creation is the
less productive, non-tradable services sectors, namely
wholesale, trade, restaurant, and accommodation sector.
Not only does the Indonesia’s economic growth become
increasingly jobless, but also less productive. Regarding
Indonesia’s demographic dividend within decades ahead,
the additional pool of labor in the coming future will tend
to unoptimalized if Indonesia’s economy is under-capacity
in providing it with highly productive jobs.

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

TABLE 1

9 9

ASEAN-5’s Competitiveness world ranks in Flexibility

7th pillar: Labor
market eiciency

Sub Pillar:
Flexibility (7A)

Cooperation in
labor-employer
relation (701)

Flexibility
of wage
determination
(702)

Hiring and iring
practices (703)

Redundancy
costs (704)

Efects of
taxation on
incentive to
work (705)

Cont.

Rank

Cont.

Rank

Cont.

Rank

Cont.

Rank

Cont.

Rank

Cont.

Rank

Cont.

Rank

SIN

1

SIN

1

SIN

2

SIN

5

SIN

3

SIN

6

SIN

4

MAL

25

MAL

29

MAL

19

MAL

33

MAL

26

MAL

110

MAL

10

THA

62

PHI

108

PHI

34

IND

106

THA

31

PHI

124

IND

27

PHI

100

THA

120

THA

37

PHI

109

IND

39

THA

135

PHI

40

IND

103

IND

133

IND

49

THA

111

PHI

117

IND

141

THA

44

Source: Global Competitiveness Index data platform, WEF, accessed in 2014.

Referring McMillan and Rodrik (2011), there are essentially
two sources of productivity growth, namely within and
structural change productivity. Within productivity growth
demonstrates the productivity enhancement within the
sectors; while structural change growth denotes labor
movement from less to more productive activity. This
paper put emphasis on labor lows from low to higher
productivity jobs, as it is a key driver of development.
Documenting the evolution and the progress of structural
change in Indonesia is undeniably a very important task
to do, as it needs to provide its people with more and
better jobs.

2

D

The main objectives of this study are to map the
structural change in Indonesia’s provinces, and identify
the drivers that distinguish the successful provinces
from the unsuccessful ones in term of structural change
growth, meaning labor movement from low to higher
productivity jobs. Chapter I presents about background
and motivation of the study, while Chapter II is the
section of literature review. Chapter III describes research
methodology and data. Chapter IV is the elaboration of
structural change mapping and regression result. Finally,
Chapter V summarizes the inding and derives the policy
implications.

LITErATurE rEvIEwS

eveloping economies are characterized by the
experiences of structural change, demonstrated
by the signiicant change of productivity within
and across sectors. Recalling Lewis (1954) dual economy
models, the income diferences between subsistence
and modern sectors will increase the employment of
modern sector. Before the competitive subsistence
sector’s wage is establisehed, labors from subsistence
sector are attracted to work in modern sector because
of higher wage, that lower the employment share in
subsistence, low-productivity agriculture sector. This
movement will increase the modern sector’s output, until
the surplus of labor from subsistence sector is depleted.
Thus, the more movement of labor into modern sectors
will generate higher productivity output, and usually
happens simultaneously with the increase in agriculture
productivity.

Harris and Todaro (1957) explains that the migration
from rural to urban area, as well as structural change
from agriculture to modern sectors, when the politically
determined minimum urban wage is imposed, in the
higher level than agricultural earnings. The structural
change and migration happen as a response of urban-rural
diferences in expected wages, with urban employment
rate as equilibrating property on the migration, which
will increase the informality.
Structural change is one of the most important parts of the
development process in most developing countries. The
movement of labor from low-productivity sectors (usually
agriculture) to higher productivity sectors contributes to
overall increase in productivity.
Furthermore, the structural change is driven by two
forces (Maddison 1987). First, the elasticity of demand for

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certain product that become more similar at given level
of income, thus reduce the demand in agriculture goods
and increase the demand for products of services and
industry. Second, the diferent of speed of technological
advance across sectors, i.e. productivity growth is slower
in service than commodity production.
Alvarez-Cuadrado and Poschke (2009) research the
structural change out of agriculture by employing
‘labor push’ and ’labor pull’ channels. The ‘labor push’
hypothesis represents the improvements in agricultural
technology combined with Engel’s law of demand, which
push resources away from agricultural sector.1 Therefore,
the firms in non-agricultural sector will increase the
employment. The ‘labor pull’ hypothesis explains the
improvements in industrial technology attracts worker
into this higher-productivity sector.
In general, Maddison (1987) and Alvarez-Cuadrado and
Poschke (2009) share similar arguments: both of their irst
argument is similar (‘labor push’ hypothesis), although the
Alvarez-Cuadrado’s (2009) second argument, ‘labor pull’
hypothesis, could be seen as an implication of Maddison’s
(1987) speed of technological advance argument.
In the result of structural change, McMillan and Rodrik
(2011) investigates, whilst the movement to higher
productivity occurs in East Asian countries, some cases
show the opposite movement could happens, such as
in Latin American and Sub-Sahara African countries.
They examines 38 countries within 1990-2005 using
decomposition of productivity into within- and structural
change-productivity growth, conclude three factors that
explain whether the structural change is in the expected
direction: (1) Countries with initial comparative advantage
in primary products are disadvantaged; (2) Countries which
keep competitive currencies encounter positive structural
change; (3) Flexible labor market system could advantage
countries to earn growth-enhancing structural change.
Pieper (2000) examines 30 developing countries within
1975 to 1984 and 1985 and 1993, observes that Asian
countries has increased their industry’s contributions
(positive structural change), whereas the opposite happens
in many countries in Latin America and Sub-Saharan Africa.

1

One of the important indings is the evidence of Asian
countries that able to increase both labor productivity and
employment in industry and a whole economy, indicating
there is no trade-of between them.
Other decomposition is presented in Ocampo et al. (2009)
which involving 57 countries within 1990-2004. It founds
that industry sector is the most gaining in productivity
in Asian Tigers (Malaysia, Singapore, South Korea, and
Taiwan), China, generated by within-productivity, and
Southeast Asia, driven by structural change-productivity.
Services become dominant contributor of South Asia, and
driven more by within-productivity. A diferent picture is
shown in Sub-Saharan Africa which demonstrates stagnant
productivity growth with low positive within-productivity
growth and negative structural change- produtivity
growth. Latin American countries show similar trend with
Asia, but experience lower within-productivty growth.
A diferent approach, by employing Total Factor Productivity
is investigated by Ngai and Pissarides (2007). They show
various TFP growth across sectors predict employment
changes in sectors that consistent with low substitutability
between inal good produced by each sector. In balance
aggregate growth, there is a shifting of employment from
sector with high technological progress into lower growth
sector, while in the limit, all employment converges into
two: sector producing capital goods and sector with
lowest rate of productivity growth. Their indings also
show the decrease of agriculture’s employment share,
the increase and decline of manufacturing share, and the
rise of service share.
The impact of technological changes is founded by
Fagerberg (2000). He investigates to see structural change
in technology side. He studies the productivity of 39
countries between 1973 and 1990, found that structural
changes are more likely to be inluenced by technological
changes than the period before, suggesting the inclusion
of technological progress could advantage the growth.
The speciic structural change investigation in Indonesia
is lacking. Hill et al. (2008) briely shows some progresses
in Indonesian structural change between 1975 and
2004. They found that the provinces with agriculture

Engel’s law states that as income rises, the proportion of expenditure on foods are decreasing, even the actual expenditure on food rises.

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

dependency (more than one-third of GRP) shrunk from
21 provinces in 1975 to only eight provinces in 2004.
Further, in manufacturing sectors, the provinces progressed
to produce more manufacturing output at least 20% of
GRP from zero province in 1975 to seven provinces in
2004. Lastly, the services sectors also shows progressive

3

1111

growth. Started by only two provinces with one-half of
GRP from services sectors in 1975, ive provinces now in
this group, whilst several comes up approaching. They
also found weak correlation between non-mining growth
and structural change in Indonesia, but becomes stronger
when mining sector is included.

METHODOLOgy AND DATA

3.1 Methodology
3.1.1 Structural Changes
Decomposition

3.1.2 Determinant of Structural
Change in Indonesia, period
2001-2011

T

his research borrows McMillan and Rodrik (2011)
methodology that simply decompose productivity
growth into two: (1) productivity growth ‘within’
sector, and (2) structural change productivity growth. The
decomposition is written as:
(1)

and
are economy-wide and sectoral
Where
labor productivity level, respectively.
represents the
employment share of sector i in time t. ∆ denotes the
change of both productivity and employment share
between time t-k and t. The irst term is productivity
“within” term whilst the second term denotes “structural
change” term.
The compartmentalization of those two components is
very useful in tracking the source of productivity growth,
whether it is from productivity enhancement within the
industry or from the labor re-allocation efect across diferent
economic sectors. The positive sign of within productivity
growth demonstrate the productivity enhancement within
the sectors, i.e. the sector earns more output by increasing
eiciency, mechanization, and improved know-how; while
positive structural change growth denotes labor movement
from less to more productive activity. Positive structural
change growth means that the country/region is on the
right track of development process and able to diversify
away from agriculture and other traditional activities with
low productivity, towards modern economic activities with
higher productivity (e.g. manufacturing, services, etc.). In
this study, the speed of the structural change diferentiates
successful provinces from unsuccessful ones.

Following McMillan and Rodrik (2011), this research
employs one determinant in that relevant for this provincial
study in Indonesia: agriculture share in employment. This
research uses primary sector share in GDP (i.e. agriculture
and mining sector) as a modiication of their raw material
share in export, due to domestic economic context on
the research. the using of share to GDP to igure the
dependency into certain sectors similar with approach
by Hill et al (2009).
This paper captures the role of tradable industries by
adding provincial trade openness. High trade openness
could positively or negatively related with structural
changes. Positive correlation happens if the export
dominates more the domestic business and employs labor
from lower productivity’s sectors. In contrast, negative
correlation happens when domestic import-competing
business will lose its competitiveness, thus discouraging
the growth-enhancing structural change.
This paper also tests the variable that mentioned in
McMillan and Rodrik (2011) but insigniicant: institutional
quality. In this study, institutional quality is represented by
share of public, law, and order function expenditure to
total government expenditure in each province. Higher
public, law, and order expenditure expectantly represents
higher attention of institutional reform by government,
which will encourage structural change by fairer assistance
on negotiation of industrial relation issues, as well as
efectiveness in delivering infrastructure and education
development in provincial level.

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The employment rigidity variable is captured by the
variation of minimum wage as a barrier for irm to recruit
new employee. The sharp increases of minimum wage
prevent job creation and retention, and reduction in formal
employment (rising agriculture sector share), especially if
the economy is dominated by small irms (Del Carpio et al.
2012, Mason & Baptist 1996). These will negatively afects
structural change. Other variable that could represent
rigidity is severance pay, but since its rate is determined
nationally, it is impossible to capture the variation.
Finally, this research adds infrastructure and education
factors as determinant of structural change. Intuitively,
better public infrastructure will give a better access for
employee to move into higher productivity sector and
irm to recruit more workers from subsistence sectors,
whilst the higher logistic cost will discourage irms to
expand their employment. The evidence in China shows
that structural change is positively correlated with physical
infrastructure, besides human capital and capital stock
(Biggeri 2010).
Education is employed as determinant because of its role
to upgrading technical absorption that facilitate labor to
be qualiied in higher productivity jobs. It is strengthened
by Artuç et al. (2013), proving that labor mobility
cost—which becomes barrier of structural changes—is
negatively correlated with education. A clearer evidence
comes from Lee and Malin (2013) showing that 11% of
aggregate growth of productivity in China comes from
education, consisting 9% from labor reallocation and 2%
of increase of within-sector human capital. This paper

4

uses Barro and Lee (1993) calculation method of mean
years of schooling.

3.2 Data
This paper uses Indonesian provincial data from 20012011 from World Bank’s Indonesia Database for Policy and
Economic Research (INDO-DAPOER), National Survey of
Labor Force (SAKERNAS), and Statistic of Indonesia from
Central Statistic Agency of Indonesia (BPS). It accounts
30 provinces used in 2001 and 2011, adopting the 33
provinces at the latter years into 30 provinces to create a
balanced panel data2. This research uses period between
2001 and 2011 to see the recent trend of Indonesian
productivity growth during the economics emergence
after Asian Financial Crisis that followed by the fall of
authoritarian regime. The period is also interesting,
especially for provincial study, because Decentralization
Act is legislated in 1999, thus increases local governments’
(including province’s) discretion unlike years before. In
2003, The Manpower Act is enacted, starting a period of
more stringent labor protection that increases employment
rigidity in higher level, e.g. by the ever-increasing minimum
wage among provinces.
This research classiies nine sectors with International
Standard Industrial Classiication (ISIC) revision 2.3 For
Indonesian historical comparison, this research using
database from 10-Sector Productivity Database, by Timmer
and de Vries (2009). For regression, this research shows the
complete description of the dependent and independent
variables that can be seen in Appendix A.

THE rESuLT

T

his section will be divided in two main parts, the
irst part is the mapping on structural change
and productivity growth in Indonesia (national
and provincial level) from 2001-2011, while the second
part is devoted to analyze the determinants of structural
change, or in other words, the labor movement from low
to high productivity sectors.

2

4.1. The Pattern of Productivity
Growth and Structural Change
in Indonesia
National Level
Indonesia experiences positive and increasing productivity
growth from period to period. In 2001-2011, Indonesia

New provinces are created after 2001: West Papua (2003) from Papua, Riau Islands (2004) from Riau, and West Sulawesi (2004) from South Sulawesi. Thus, we
define the provinces in 2011: Papua (West Papua and Papua), Riau (Riau and Riau Island), and South Sulawesi (South Sulawesi and West Sulawesi).

3

See the Appendix B for complete description of ISIC rev. 2

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

FIgURE 2

Decomposition of Labor Productivity Growth in Indonesia 1971-2011

2001-2011

1986-2001

1313

2.370%

0.961%

1.114%

within

1.469%

structural

1971-1986

0.000%

0.995%

0.500%

1.300%

1.000%

1.500%

2.000%

2.500%

3.000%

3.500%

Note: Data from 1971 to 2000 is from Groningen Growth and Development Centre 10-sector database, June 2007, http://www.
ggdc.net/, de Vries and Timmer (2007) using ISIC rev.3 classification; while the 2001 to 2011 data is aggregated from provincial
data as provided by The World Bank, INDO-DAPOER, using ISIC rev. 2. The difference between ISIC rev. 2 and rev. 3 mostly on the
detail, not on the aggregate classification, thus making them somewhat comparable, especially in aggregate level.
Source: authors’ calculation based on Timmer and de Vries (2007); The World Bank, INDO-DAPOER (accessed in 2014).

experienced notable productivity growth, that is, 3.33%
per annum, which mostly comes from within component
(2.37% per annum) of productivity growth, rather than the
structural changes (0.96% per annum). The composition
of productivity growth is quite reversed, if it is compared
with the productivity growth in 1971 to 2000. As depicted
in Figure 2, from the period of 1971-1985 to 1986-2000,
the structural change component is always higher than
the within component. The positive sign of structural
change component in 2001-2011 means that Indonesia,
in general, is still on the “right track” of the development
process, as it succeeds on moving its employment away
from low productivity jobs (e.g. agriculture) towards higher
productivity jobs (e.g. services). However, the decreasing
trend of structural change component indicates that the
pace of the economy to move its labor away from
low to higher productivity job becomes slower time
by time.
The economic sectors disaggregation of labor productivity
growth decomposition can be classiied into three groups.
The first group is the sectors that have both positive sign
on within and structural change component, while the
second groups is the sectors which experienced growth
enhancing structural change (positive structural change)

yet having negative within productivity component. The
third (last) group comprises of the economic sectors which
have positive within component, yet experiencing growthreducing structural change (negative structural change).
This study inds no sectors having both negative within
and structural change component.
There are 4 sectors which have both positive sign
on within and structural change component, namely
public utilities; construction; trade, restaurant and
accommodation; as well as government (social)
sectors. The government, construction and public
utilities sectors are related to each other. The positive
growth of within and structural change indicates the
active expansion of government/public works, especially
in the area of basic infrastructure/delivery, such as road
construction, electricity, and water supply. Such expansion
contributes positively to productivity growth and attracts
more employment. Trade, restaurant, and accommodation
sector experiences highest productivity growth; its within
productivity growth is the highest among all, while
the structural change growth is the second highest,
after financial, insurance, and real estate sector. The
strong productivity growth of the trade, restaurant, and
accommodation sector as well as its ability to absorb more

14

FIgURE 3

APINDO Policy Series

Decomposition of Labor Productivity Growth in Indonesia 1971-2011: Sectoral Figures

Note: see the notes in Figure 2
Source: authors’ calculation based on de Vries and Timmer (2007); The World Bank, INDO-DAPOER (accessed in 2014).

employment than the others are the logical consequences
of Indonesia’s increasing volume of trade, induced by many
FTAs signed in recent years, as well as its increasingly
competitive and attractive tourism-travel destination in the
world. Robust trade sector productivity is also linear with
the fact that most of Indonesia’s capital cities has rapidly
transformed themselves into more competitive servicestrade city (e.g. Jakarta, Surabaya, Medan and Makassar)
The economic sectors which have positive sign on
structural change component, but experiencing
negative within-productivity growth are miningquarrying, and inancial, insurance, and real estate
sectors. Both sectors are among the well-paid, high
productivity, and most attractive employment destination
for the workers. In fact, in 2001-2011 period, inancial,
real estate and insurance sectors experience the highest
growth on the structural change, where its employment
share in 2011 is almost doubled than that of 2001. Yet,
they now experience diminishing rate of return on their
productivity, meaning that the increase of output is much
lower than the additional level of input (labor) coming to
that sectors. In other words, these sectors are ‘overcrowded’
by surge of labor coming from lower productivity sector

so that its eiciency depleted. It is even worse for mining
and quarrying sector, that its negative within productivity
growth surpasses its structural change growth. It means,
from 2001 to 2011, the net outcome of absorbing more
labor to mining and quarrying sector tends to create
ineiciency and reduce productivity. It is fair to say that
the sector is in the middle of their saturation point.
The last group of sector is the sectors that have
positive sign on their within productivity growth,
but experiencing negative structural change growth
(growth-reducing structural change), comprising of
agriculture, transportation and manufacturing sectors.
Agriculture sector expectedly experiences negative
structural change, as it is the main source of workers
for other sectors. It is not the case of negative structural
change growth in transportation and manufacturing
sector, as they are not a natural source of workers for other
sectors. Growth reducing structural change, yet signiicant
positive within productivity growth in transportation
and telecommunication sector suggests that there
are now more eicient operator in transportation and
telecommunication services available domestically. It is
quite logical to see that eiciency sometimes requires labor

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

restructuring, and at the same time, greater utilization of
high technological and capital content.
The negative structural change growth (growth-reducing
structural change) in manufacturing sector from 2001
to 2011 is the most striking inding in this study. Since
1971, at least until the beginning of 2000’s, manufacturing
sector has always recorded positive signiicant growth
both in within and structural change component. In 19711986, manufacturing productivity grew at a considerable
level, that is, 0.73% per annum. While in 1986 to 2001,
manufacturing grew even higher at 1.23% per annum and
is among the major absorber of surplus of workers around
that time. In 2001-2011, the manufacturing productivity
growth has reduced notably to only around 0.58% per
annum, and at the same time, the portion of labor working
in the manufacturing sector has been reduced (see
Figure 3). From the earlier inding, it is implied that the
structural change has begun to slower from time to time.
The negative structural change growth in manufacturing
sector provides additional insight that the recent structural
transformation in Indonesia has not only been slower, but
also tends to left manufacturing sector behind.
This inding is a bad sign for Indonesia, as manufacturing
sector is the only possible, yet productive sector which
can absorb abundant additional pool of labor in the years
TABLE 2

1515

ahead. If Indonesia seeks to transform its economy into
a higher path of productivity without losing the capacity
to absorb massive new employment, it has to strengthen
manufacturing base in the country. The progress of
services sectors is inevitable; but losing manufacturing
base while there will be one-time “demographic dividend”
doesn’t seem quite strategic.

Provincial level
The general labor productivity igure in Indonesia in 2011
showed that 1 unit of labor in Indonesia, averagely, can
produce around Rp 21.53 million per year. The highest
and lowest average productivity belong to DKI Jakarta
and Nusa Tenggara Timur (NTT) by 92 and 6.3 million
Rupiah, respectively. This relects an extreme disparity of
productivity between provinces. Manufacturing, inance,
mining, and public utilities sectors are among the highest
productivity job in most of Indonesia’s provinces, while
agriculture sector is expectedly the least productive
activity.
The most productive province in doing the primary
(resource-based) economic activity mostly located in
Sumatera island, namely Bangka-Belitung Islands for
agriculture, as well as Riau (and Riau Islands) for mining
and quarrying activities. Public utilities sector is the

Summary Statistics on Sectoral Labor Productivity

Sector

average sectoral labor
productivity (Million IDR)

Maximum Sectoral Labor
Productivity (Million IDR)
Province

Minimum Sectoral Labor
Productivity (Million IDR)

Labor
Productivity

Province

Labor
Productivity

Agriculture, Hunting, Forestry, and
Fishing

Agr

8.498

Bangka Belitung
Islands

17.067

NTT

3.500

Mining and Quarrying

Min

118.764

kepri (riau)

950.269

Banten

1.613

Manufacturing

Man

38.943

kaltim

342.387

NTT

1.516

Utilities (Electricity, Gas, and
Water)

Uti

107.307

West Java

211.704

Maluku

8.970

Construction

Con

22.486

DKI Jakarta

270.524

North Maluku

3.314

Wholesale and Retail Trade,
Hotels, and Restaurants

Trd

21.280

DKI Jakarta

56.235

Gorontalo

7.016

Transport, Storage, and
Communications

Tra

37.827

DKI Jakarta

135.356

North Maluku

9.407

Finance, Insurance, Real Estate,
and Business Service

Fin

79.608

DKI Jakarta

265.843

Banten

17.310

Community, Social, Personal and
Government

Soc

13.291

DKI Jakarta

41.185

North Maluku

3.538

Economy-Wide

Sum

21.553

DKI Jakarta

92.022

NTT

6.322

Source: authors’ calculation based on de Vries and Timmer (2007); The World Bank, INDO-DAPOER (accessed in 2014).

16

APINDO Policy Series

FIgURE 4

‘Within’ and ‘Structural Change’ Productivity Growth, 2001-2011

Notes: See table 4 for the provinces’ code used in graph
Source: authors’ calculation based on de Vries and Timmer (2007); The World Bank, INDO-DAPOER (accessed in 2014).

most productive in West Java, while East Kalimantan is
recorded as the most productive region for conducting
manufacturing activities. Jakarta, as a services capital
of Indonesia, expectedly showed the highest labor
productivity score for the entire services activity in
Indonesia (see Table 2).
There are generally two types of region in Indonesia, the
one is the region which is successful in moving its labor
away from low to higher productivity jobs, and the other
one is the region that fails to do so. Almost the entire
province in Indonesia is considerably successful in moving
its labor away from low to high productivity sectors, or
in other words, experiencing positive structural change
growth, except for Banten, Jambi, West Kalimantan, Central
Kalimantan, Bangka Belitung Islands, North Maluku, and
NTB—that are experiencing negative structural change
growth in the period of 2001-2011 (see Table 3). Among
the successful region, there are provinces which records
positive within-productivity growth, and there are regions
showing the opposite sign (negative within-productivity
growth). Aceh, Riau (and Riau Islands), East Kalimantan, and
Papua (and West Papua) are among the provinces having

4

negative within productivity growth. This study inds no
single province experiencing both negative within and
structural change growth (see Figure 4).
This study identifies such a significant gap on the
performance of labor productivity and structural change/
transformation growth between the provinces. The next
section will discuss deeper on the driver/enabling factors
that might explain why a region are doing quite well,
while the other is not, in term of structural transformation/
change, that is to moving its labor away from low to higher
productivity jobs. From the regression result, this paper
derives policy implication needed to promote provincial
structural change/transformation back on the right track.

4.2 Determinant of Structural Changes
Before formal regression equation is run, we conduct
several test on the variable and model speciication. The
result suggests that the model is free from the classical
problems such as multicollinearity, heteroscedasticity, as
well as omitted variable.4

Breusch-Pagan/Cook-Weisberg test for heteroscedasticity rejects alternative hypothesis (H1), meaning that the model free from heteroscedasticity problem.
VIF test shows a number that is not between the range to be judged as having multicollinearity problem, i.e. 1.51 (mean VIF). The individuals VIF value are
also not in the multicollinearity’s range. The model are free from omitted variable problem, which is indicated by Ramsey RESET test accepting null hypothesis
(model has no omitted variables).

TABLE 3

No

Summary Statistics

Province

1

Nanggroe Aceh
Darussalam

2
3
4

Riau + Riau Islands

5
6

Code

Economywide Labor
Productivity

Sector with Highest Labor
Productivity

Sector with Lowest Labor
Productivity

Compound Annual growth Rate of Economicwide Productivity

Sector

Labor
Productivity

Sector

Labor
Productivity

annual growth
rate of ‘within’
productivity

annual growth
rate of ‘structural
change’
productivity

annual growth
rate of total
productivity

18.775

Min

222.583

Agr

10.408

-1.68%

0.47%

-1.21%

North Sumatera

NSM

21.412

Fin

84.503

Agr

11.325

2.42%

1.20%

3.61%

West Sumatera

WSM

19.941

Tra

58.687

Agr

11.649

2.58%

1.09%

3.67%

RIA

45.671

Min

950.269

Soc

12.792

-2.15%

1.52%

-0.63%

Jambi

JAM

13.215

Min

122.888

Soc

7.171

2.80%

-0.01%

2.79%

South Sumatera

SSM

19.140

Min

345.587

Agr

6.475

1.76%

1.61%

3.37%

7

Bangka Belitung Islands

BBE

19.652

Man

75.596

Soc

9.705

2.42%

-1.01%

1.41%

8

Bengkulu

BEN

10.161

Min

33.485

Con

6.331

2.21%

1.00%

3.21%

9

Lampung

LAM

11.733

Fin

102.478

Soc

7.148

2.77%

1.13%

3.90%

10

Banten

BAN

20.798

Uti

190.702

Min

1.613

3.39%

-0.34%

3.05%

11

DKI Jakarta

DKI

92.022

Con

270.524

Agr

10.086

2.21%

0.58%

2.79%

12

West Java

WJA

19.657

Uti

211.704

Soc

8.746

2.83%

0.66%

3.50%

13

Central Java

CJA

12.457

Uti

58.699

Agr

6.584

4.36%

0.32%

4.68%

14

D I Yogyakarta

DIY

12.304

Uti

47.385

Agr

8.249

2.77%

0.85%

3.62%

15

East Java

EJA

19.376

Uti

202.143

Agr

6.998

3.94%

0.57%

4.51%

16

Bali

BAL

13.950

Uti

68.644

Con

6.658

2.93%

0.51%

3.44%

17

Nusa Tenggara Barat

NTB

9.903

Min

81.312

Agr

5.420

2.93%

-0.10%

2.83%

18

Nusa Tenggara Timur

NTT

6.322

Fin

24.765

Man

1.516

2.28%

1.35%

3.63%

19

West Kalimantan

WKA

14.972

Fin

86.082

Agr

6.119

2.57%

-0.28%

2.29%

20

South Kalimantan

SKA

17.838

Min

97.692

Agr

9.961

2.50%

0.06%

2.56%

21

Central Kalimantan

CKA

18.159

Fin

89.253

Agr

9.912

2.68%

-0.47%

2.21%

22

East Kalimantan

EKA

72.435

Man

342.387

Soc

8.294

-1.59%

0.25%

-1.34%

23

Gorontalo

GOR

7.056

Uti

102.932

Min

2.356

3.06%

0.99%

4.04%

24

North Sulawesi

NSU

19.920

Fin

58.127

Agr

11.083

3.20%

0.95%

4.15%

25

Central Sulawesi

CSU

15.255

Uti

74.495

Agr

11.499

3.55%

1.15%

4.70%

26

South Sulawesi + West
Sulawesi

WSU

15.424

Min

121.204

Agr

9.612

2.07%

1.59%

3.66%

27

Southeast Sulawesi

SSU

12.334

Fin

71.251

Agr

7.851

2.75%

2.17%

4.93%

28

North Maluku

NMA

7.339

Fin

40.502

Con

3.314

3.09%

-1.16%

1.92%

29

Maluku

MAL

6.933

Fin

29.287

Con

3.735

0.14%

1.16%

1.30%

30

Papua + West Papua

PAP

18.261

Min

195.823

Agr

4.914

-3.67%

0.80%

-2.87%

IDN

21.553

Min

118.764

Agr

8.498

2.37%

0.96%

3.33%

Indonesia

Source: Authors’ calculation based on The World Bank, INDO-DAPOER (accessed 2014)

1717

Note: All numbers are for 2011.Currency is in constant 2000 IDR. Growths are in annual rate, between 2001 and 2011. Abbreviations are follows: (Agr) Agriculture; (min) Mining, (Man) Manufacturing; (Uti) Public
Utilities; (Con) Construction; (Tra) Wholesale and Trade; (Tra) Transport and Communication; (Fin) Finance and Business Service; (Soc) Community , Social, and Government Services

Labor Movement from Low to High Productivity Sector:
Evidence from Indonesia’s Provincial Data

NAD

APINDO Policy Series

18

TABLE 4

Regression results

Dep. var: annual structural-change growth
agricultural share in employment

annual growth of primary sectors share in GDP

annual growth of institution spending share

annual growth of infrastructure spending

primary education

openness to trade

minimum wage growth

East-Indonesia dummy

constant

variables
0.033 ***
(0.095)
-0.125 *
(0.072)
0.020 ***
(0.005)
-0.006
(0.005)
0.010 **
(0.004)
-0.006
(0.004)
-